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View all- Zhou HHuang SXu Y(2025)UA-FER: Uncertainty-aware representation learning for facial expression recognitionNeurocomputing10.1016/j.neucom.2024.129261621(129261)Online publication date: Mar-2025
Zero-shot learning (ZSL) aims to recognize unseen categories without corresponding training samples, which is a practical yet challenging task in computer vision and pattern recognition community. Current state-of-the-art locality-based ZSL ...
Zero-shot learning (ZSL) aims to learn a projection function from a visual feature space to a semantic embedding space or reverse. The main challenge of ZSL is the domain shift problem where the unseen test data has a large gap with ...
Zero-shot learning (ZSL) aims to bridge the knowledge transfer via available semantic representations (e.g., attributes) between labeled source instances of seen classes and unlabelled target instances of unseen classes. Most existing ZSL approaches ...
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